Perfusion data is used to diagnose a wide range of pathologies in the human body by showing the flow of injected contrast agents. A perfusion study comprises several acquisitions, typically one before the injection and one or more acquisitions at time intervals after the injection. Studies show the spread of contrast agent in different tissue.
In order to detect subtle changes, the different time series resulting from the acquisitions have to be combined in an appropriate way so that the enhancement attributable to the contrast agent can be calculated locally and visualized. Typically, a form of registration, deformable or rigid, is used to compensate for patient motion. Then the data can be compared, subtracted, etc., and the flow information can be extracted. The result of the flow calculation is either displayed in separate views, or it is merged back into one of the series to provide the user with anatomical context. This merging is usually done for the complete image, using a blending.
As an example, the calculation of the Hepatic perfusion index is cited. In the example, three phases are acquired: a Native phase N, without contrast, an Arterial phase A, wherein contrast has entered the arterial system, and a Venous phase V, wherein contrast has filled the venous system. Then these different time series are deformed to compensate for patient motion, including the effects of breathing. After deformation, the time series are in the same coordinate system and can be compared voxel by voxel. The Hepatic perfusion index HPI is then calculated asHPI=(A−N)/Max(A−N, V−N).
This value is displayed in a color-coded scheme. It has been shown in publications that the HPI improves the detection of subtle changes in the liver related to HCC (liver tumors). See, for example, Kim K W, Lee J M, Klotz E, Park H S, Lee D H, Kim J Y, Kim S J, Kim S H, Lee J Y, Han J K, Choi Bl, “Quantitative CT Color Mapping of the Arterial Enhancement Fraction of the Liver to Detect Hepatocellular Carcinoma”, Radiology, in press: Radiology: Volume 250: Number 2; February 2009. It is noted that co-author E. Klotz is a named inventor in the present application.
However the color coded image generally also shows enhancement outside the liver, where it is typically not of any value and, in fact, may tend to obscure anatomical information and/or landmarks and can distract the focus of attention of the viewer. Even inside the target organ, such as a liver, the arteries are enhanced as well, making it necessary to inspect carefully to distinguish lesions from arteries. See FIG. 2 for an example of an image without application of the present invention.